J Lipid Atheroscler.  2020 Jan;9(1):110-123. 10.12997/jla.2020.9.1.110.

Quantifications of Lipid Kinetics In Vivo Using Stable Isotope Tracer Methodology

• Kim IY
• Park S
• Jang J
• Wolfe RR

• KMID: 2470804
• DOI: http://doi.org/10.12997/jla.2020.9.1.110

Abstract

Like other bodily materials, lipids such as plasma triacylglycerol, cholesterols, and free fatty acids are in a dynamic state of constant turnover (i.e., synthesis, breakdown, oxidation, and/or conversion to other compounds) as essential processes for achieving dynamic homeostasis in the body. However, dysregulation of lipid turnover can lead to clinical conditions such as obesity, fatty liver disease, and dyslipidemia. Assessment of "snap-shot" information on lipid metabolism (e.g., tissue contents of lipids, abundance of mRNA and protein and/or signaling molecules) are often used in clinical and research settings, and can help to understand one's health and disease status. However, such "snapshots" do not provide critical information on dynamic nature of lipid metabolism, and therefore may miss "true" origin of the dysregulation implicated in related diseases. In this regard, stable isotope tracer methodology can provide the in vivo kinetic information of lipid metabolism. Combining with "static" information, knowledge of lipid kinetics can enable the acquisition of in depth understanding of lipid metabolism in relation to various health and disease status. This in turn facilitates the development of effective therapeutic approaches (e.g., exercise, nutrition, and/or drugs). In this review we will discuss 1) the importance of obtaining kinetic information for a better understanding of lipid metabolism, 2) basic principles of stable isotope tracer methodologies that enable exploration of "lipid kinetics" in vivo, and 3) quantification of some aspects of lipid kinetics in vivo with numerical examples.

Keyword

Lipid metabolism; Substrate turnover, Dyslipidemia; Mass spectrometry

MeSH Terms

Cholesterol
Dyslipidemias
Fatty Acids, Nonesterified
Fatty Liver
Homeostasis
Kinetics*
Lipid Metabolism
Mass Spectrometry
Obesity
Plasma
RNA, Messenger
Triglycerides
Cholesterol
Fatty Acids, Nonesterified
RNA, Messenger
Triglycerides

Figure

• 

  Fig. 1 The volume of water (i.e., water pool size) in the tank is determined by the balance of 2 kinetic variables: 1) rates of appearance (Ra) into and 2) disappearance (Rd) of water from the tank. The water pool size can change if an imbalance between the rates exists, regardless of their absolute rates. Furthermore, absolute rate of the water turnover may affect the quality of the water (i.e., “metabolic health”).

• 

  Fig. 2 TAG pool size (concentration×volume of distribution) in the tissue compartment (e.g., plasma, liver, and muscle) is determined by the balance between rates of appearance (Ra), or secretion and disappearance (Rd) or clearance of VLDL-TG (i.e., TAG turnover), regardless of their absolute rates. In tank A, the TAG pool size stays same due to the close match between Ra and Rd. However, both tanks B and C are in hypertriglyceridemic states to an identical magnitude despite different rates of each side of TAG turnover (i.e., Ra and Rd), underlying the importance of assessing dynamics of lipid metabolism in addition to the “static” snap-shot information (e.g., measurement of pool size). TAG, triacylglycerol; VLDL-TAG, very low-density lipoprotein-triacylglycerol.

• 

  Fig. 3 Schematic of potential sites of dysregulation of lipid metabolism to which stable isotope tracers can be applied to obtaining dynamic nature of lipid kinetics. FA-CoA, fatty acyl CoA; IMTAG, intramuscular triacylglycerol; FFA, free fatty acids; G-3-P, glycerol 3 phosphate; VLDL, very low-density lipoprotein; DNL, de novo lipogenesis; GNG, gluconeogenesis; TAG, triacylglycerol.

• 

  Fig. 4 Flow diagram showing the sequence of events in a stable isotope tracer infusion study for assessing metabolic kinetics such as lipids. Qualified subjects take part in tracer infusion studies before, during, and/or after an intervention. During the tracer infusion study, subjects receive a primed continuous infusion of tracer(s) at a predetermined rate (F) during a specified time period before and during which tissue samples (e.g., plasma) are collected for determination of enrichments by GC- or LC-MS. In vivo metabolic substrate kinetics (e.g., Ra FFA) are calculated based on appropriate tracer models using F and enrichments at steady state (Ep, dotted blue line in “stable isotope tracer infusion study”). The number of samples collected is dependent on the study design. TTR, tracer to tracee ratio; Ra, rate of appearance; FSR, fractional synthesis rate; GC-MS, gas chromatography-mass spectrometry; LC-MS, liquid chromatography-mass spectrometry; FFA, free fatty acid; TAG, triacylglycerol.

• 

  Fig. 5 Schematic principle of the tracer dilution model for assessing in vivo metabolic flux rate. In a steady state before introduction of tracer(s) Ra tracee (black circle) is equal to Rd tracee, both of which are unknown (A). To determine tracee kinetics, a (primed) constant infusion of tracer (e.g., palmitate, red circle) is performed during which tracer concentration relative to tracee concentration (i.e., TTR) rises to plateau where tracer infusion rate (F) is also equal to rate of tracer palmitate leaving the compartment (B). The time course of changes in isotopic enrichment after constant infusion of tracer is shown in (C). Based on these relations, it is derived that TTR at plateau is equal to ratio of F to Ra Tracee. By rearranging the equation, it is derived that Ra tracee is equal to F divided by TTR at plateau (i.e., Ep) (D). TTR, tracer to tracee ratio.

• 

  Fig. 6 Schematic principle of the tracer incorporation model of assessing in vivo metabolic flux rate. At an initial time period of isotopic steady state (A), both labeled and unlabeled precursors enter a synthetic pathway in proportion to their relative ratio (1:1 in this case) and enrichment of the product rises at a constant rate. However, as time goes to infinity, product enrichment ultimately reaches precursor enrichment (B). Both conditions (A, B) are described with respect to changes in enrichment of precursor and product while tissue samples are collected somewhere between these 2 (C). Fractional synthesis rate (FSR, %/time), defined as percent of pool size that has been newly synthesized for a given time, can be estimated by dividing changes in product enrichment by steady state precursor enrichment and time, multiplied by 100. To derive absolute synthesis rates, FSR needs to be multiplied by pool size. Same principle can be used for assessing synthesis of lipids such as rates of de novo lipogenesis and TAG synthesis. FSR, fractional synthesis rate; TAG, triacylglycerol; TTR, tracer to tracee ratio.

Reference

1. Schoenheimer R. The dynamic state of body constituents. Cambridge (MA): Harvard University Express;1946.

2. Schoenheimer R, Rittenberg D. Deuterium as an indicator in the study of intermediary metabolism: VI. Synthesis and destruction of fatty acids in the organism. J Biol Chem. 1937; 114:381–396.

3. Rittenberg D, Schoenheimer R. Deuterium as an indicator in the study of intermediary metabolism: XI. Further studies on the biological uptake of deuterium into organic substances, with special reference to fat and cholesterol formation. J Biol Chem. 1937; 121:235–253.

4. Kim IY, Park S, Trombold JR, Coyle EF. Effects of moderate- and intermittent low-intensity exercise on postprandial lipemia. Med Sci Sports Exerc. 2014; 46:1882–1890.

5. Kim IY, Park S, Chou TH, Trombold JR, Coyle EF. Prolonged sitting negatively affects the postprandial plasma triglyceride-lowering effect of acute exercise. Am J Physiol Endocrinol Metab. 2016; 311:E891–E898.

6. Bansal S, Buring JE, Rifai N, Mora S, Sacks FM, Ridker PM. Fasting compared with nonfasting triglycerides and risk of cardiovascular events in women. JAMA. 2007; 298:309–316.

7. Bukhari SS, Phillips BE, Wilkinson DJ, Limb MC, Rankin D, Mitchell WK, et al. Intake of low-dose leucine-rich essential amino acids stimulates muscle anabolism equivalently to bolus whey protein in older women at rest and after exercise. Am J Physiol Endocrinol Metab. 2015; 308:E1056–E1065.

8. Perry RJ, Wang Y, Cline GW, Rabin-Court A, Song JD, Dufour S, et al. Leptin mediates a glucose-fatty acid cycle to maintain glucose homeostasis in starvation. Cell. 2018; 172:234–248.e17.

9. Neinast MD, Jang C, Hui S, Murashige DS, Chu Q, Morscher RJ, et al. Quantitative analysis of the whole-body metabolic fate of branched-chain amino acids. Cell Metab. 2019; 29:417–429.e4.

10. Hellerstein MK. In vivo measurement of fluxes through metabolic pathways: the missing link in functional genomics and pharmaceutical research. Annu Rev Nutr. 2003; 23:379–402.

11. McGuire EA, Helderman JH, Tobin JD, Andres R, Berman M. Effects of arterial versus venous sampling on analysis of glucose kinetics in man. J Appl Physiol. 1976; 41:565–573.

12. Goodpaster BH, Wolfe RR, Kelley DE. Effects of obesity on substrate utilization during exercise. Obes Res. 2002; 10:575–584.

13. Kim IY, Williams RH, Schutzler SE, Lasley CJ, Bodenner DL, Wolfe RR, et al. Acute lysine supplementation does not improve hepatic or peripheral insulin sensitivity in older, overweight individuals. Nutr Metab (Lond). 2014; 11:49.

14. Kim IY, Schutzler SE, Azhar G, Wolfe RR, Ferrando AA, Coker RH. Short term elevation in dietary protein intake does not worsen insulin resistance or lipids in older adults with metabolic syndrome: a randomized-controlled trial. BMC Nutr. 2017; 3:33.

15. Chopra S, Rathore A, Younas H, Pham LV, Gu C, Beselman A, et al. Obstructive sleep apnea dynamically increases nocturnal plasma free fatty acids, glucose, and cortisol during sleep. J Clin Endocrinol Metab. 2017; 102:3172–3181.

16. Gjedsted J, Buhl M, Nielsen S, Schmitz O, Vestergaard ET, Tønnesen E, et al. Effects of adrenaline on lactate, glucose, lipid and protein metabolism in the placebo controlled bilaterally perfused human leg. Acta Physiol (Oxf). 2011; 202:641–648.

17. Kim IY, Shin YA, Schutzler SE, Azhar G, Wolfe RR, Ferrando AA. Quality of meal protein determines anabolic response in older adults. Clin Nutr. 2018; 37:2076–2083.

18. Kim IY, Schutzler S, Schrader A, Spencer HJ, Azhar G, Ferrando AA, et al. The anabolic response to a meal containing different amounts of protein is not limited by the maximal stimulation of protein synthesis in healthy young adults. Am J Physiol Endocrinol Metab. 2016; 310:E73–E80.

19. Kim IY, Park S, Smeets ET, Schutzler S, Azhar G, Wei JY, et al. Consumption of a specially-formulated mixture of essential amino acids promotes gain in whole-body protein to a greater extent than a complete meal replacement in older women with heart failure. Nutrients. 2019; 11:E1360.

20. Kim IY, Schutzler S, Schrader A, Spencer H, Kortebein P, Deutz NE, et al. Quantity of dietary protein intake, but not pattern of intake, affects net protein balance primarily through differences in protein synthesis in older adults. Am J Physiol Endocrinol Metab. 2015; 308:E21–E28.

21. de Betue CT, Joosten KF, Deutz NE, Vreugdenhil AC, van Waardenburg DA. Arginine appearance and nitric oxide synthesis in critically ill infants can be increased with a protein-energy-enriched enteral formula. Am J Clin Nutr. 2013; 98:907–916.

22. Castillo L, Beaumier L, Ajami AM, Young VR. Whole body nitric oxide synthesis in healthy men determined from [15N] arginine-to-[15N]citrulline labeling. Proc Natl Acad Sci U S A. 1996; 93:11460–11465.

23. Kim IY, Schutzler SE, Schrader A, Spencer HJ, Azhar G, Deutz NE, et al. Acute ingestion of citrulline stimulates nitric oxide synthesis but does not increase blood flow in healthy young and older adults with heart failure. Am J Physiol Endocrinol Metab. 2015; 309:E915–E924.

24. Kim IY, Suh SH, Lee IK, Wolfe RR. Applications of stable, nonradioactive isotope tracers in in vivo human metabolic research. Exp Mol Med. 2016; 48:e203.

25. Wolfe RR, Chinkes DL. Isotope tracers in metabolic research: principles and practice of kinetic analysis. New York (NY): Wiley-Liss;2004.

26. Mazzeo RS, Brooks GA, Schoeller DA, Budinger TF. Disposal of blood [1-13C]lactate in humans during rest and exercise. J Appl Physiol (1985). 1986; 60:232–241.

27. Kim IY, Schutzler S, Schrader AM, Spencer HJ, Azhar G, Wolfe RR, et al. Protein intake distribution pattern does not affect anabolic response, lean body mass, muscle strength or function over 8 weeks in older adults: a randomized-controlled trial. Clin Nutr. 2018; 37:488–493.

28. Martini WZ, Chinkes DL, Wolfe RR. Quantification of DNA synthesis from different pathways in cultured human fibroblasts and myocytes. Metabolism. 2004; 53:128–133.

29. Fulks RM, Li JB, Goldberg AL. Effects of insulin, glucose, and amino acids on protein turnover in rat diaphragm. J Biol Chem. 1975; 250:290–298.

30. Zhang XJ, Chinkes DL, Wu Z, Martini WZ, Wolfe RR. Fractional synthesis rates of DNA and protein in rabbit skin are not correlated. J Nutr. 2004; 134:2401–2406.

31. Brook MS, Wilkinson DJ, Mitchell WK, Lund JL, Phillips BE, Szewczyk NJ, et al. A novel D₂O tracer method to quantify RNA turnover as a biomarker of de novo ribosomal biogenesis, in vitro, in animal models, and in human skeletal muscle. Am J Physiol Endocrinol Metab. 2017; 313:E681–E689.

32. Khairallah EA, Mortimore GE. Assessment of protein turnover in perfused rat liver. Evidence for amino acid compartmentation from differential labeling of free and tRNA-gound valine. J Biol Chem. 1976; 251:1375–1384.

33. Wolfe RR, Peters EJ, Klein S, Holland OB, Rosenblatt J, Gary H Jr. Effect of short-term fasting on lipolytic responsiveness in normal and obese human subjects. Am J Physiol. 1987; 252:E189–E196.

34. Wolfe RR, Peters EJ. Lipolytic response to glucose infusion in human subjects. Am J Physiol. 1987; 252:E218–E223.

35. Greenough WB 3rd, Crespin SR, Steinberg D. Infusion of long-chain fatty acid anions by continuous-flow centrifugation. J Clin Invest. 1969; 48:1923–1933.

36. Hellerstein MK, Benowitz NL, Neese RA, Schwartz JM, Hoh R, Jacob P 3rd, et al. Effects of cigarette smoking and its cessation on lipid metabolism and energy expenditure in heavy smokers. J Clin Invest. 1994; 93:265–272.

37. Fontbonne A, Eschwège E, Cambien F, Richard JL, Ducimetière P, Thibult N, et al. Hypertriglyceridaemia as a risk factor of coronary heart disease mortality in subjects with impaired glucose tolerance or diabetes. Results from the 11-year follow-up of the Paris Prospective Study. Diabetologia. 1989; 32:300–304.

38. Roche HM, Gibney MJ. The impact of postprandial lipemia in accelerating atherothrombosis. J Cardiovasc Risk. 2000; 7:317–324.

39. Donnelly KL, Smith CI, Schwarzenberg SJ, Jessurun J, Boldt MD, Parks EJ. Sources of fatty acids stored in liver and secreted via lipoproteins in patients with nonalcoholic fatty liver disease. J Clin Invest. 2005; 115:1343–1351.

40. Sidossis LS, Coggan AR, Gastaldelli A, Wolfe RR. Pathway of free fatty acid oxidation in human subjects. Implications for tracer studies. J Clin Invest. 1995; 95:278–284.

41. Turner SM, Murphy EJ, Neese RA, Antelo F, Thomas T, Agarwal A, et al. Measurement of TG synthesis and turnover in vivo by 2H2O incorporation into the glycerol moiety and application of MIDA. Am J Physiol Endocrinol Metab. 2003; 285:E790–E803.

42. Cobelli C, Foster D, Toffolo G. Tracer kinetics in biomedical research. Boston (MA): Springer US;2002.